CDT403 Research Methodology in Natural Sciences and Engineering
Theory of Science
SCIENCE, RESEARCH, TECHNOLOGY, SOCIETY,
COMPLEXITY AND INTERDISCIPLINARITY
Gordana Dodig-Crnkovic
School of Innovation, Design and Engineering
Mälardalen University
1
THEORY OF SCIENCE
Lecture 1 INFORMATION, COMPUTATION, KNOWLEDGE AND
SCIENCE
Lecture 2 SCIENCE AND CRITICAL THINKING.
PSEUDOSCIENCE AND WISHFUL THINKING - DEMARCATION
Lecture 3 SCIENCE, RESEARCH, TECHNOLOGY, SOCIETY,
COMPLEXITY AND INTERDISCIPLINARITY
Lecture 4 VALUES AND ETHICS - PROFESSIONAL & RESEARCH
ETHICS
2
SCIENCE, RESEARCH, TECHNOLOGY
Aristotle's Distinctions between Science and Technology
Science
Technology
unchangeable
changeable
inside
outside
End
knowing the general
knowing the concrete
Activity
theoria: end in itself
poiesis: end external
Method
abstraction
modeling complexity
Process
conceptualizing
optimizing
discovery
invention
law-like statements
rule-like statements
long-term
short-term
Object
Principle of motion
Innovation form
Type of result
Time perspective
3
SCIENCE IN MICRO AND MACROCOSMOS
Levels of abstraction/Levels of organization
Sciences, Objects and Methods
http://www.youtube.com/watch?v=akbilxS1dGc&feature=related zoom in – zoom out
SCIENCE
Logic &
Mathematics
Natural Sciences
Social Sciences
Humanities
OBJECTS
DOMINATING METHOD
Simple
Reductionism (analysis)
Abstract objects:
propositions, numbers, ...
Deduction
Natural objects: physical bodies,
fields and interactions, living
organisms ...
Social objects:
human individuals, groups, society,
..
Cultural objects: human ideas,
actions and relationships, language,
artefacts…
Complex
Hypothetico-deductive method
Hypothetico-deductive method
+ Hermeneutics
Hermeneutics
Holism (synthesis)
4
SCIENCE, RESEARCH, DEVELOPMENT AND TECHNOLOGY
Research
Development
Science
Technology
5
CLASSICAL SCIENCES
LANGUAGE BASED SCHEME
Culture
(Religion, Art, …)
Logic
&
Mathematics
Natural Sciences
(Physics,
Chemistry,
Biology, …)
Social Sciences
(Economics,
Sociology,
Anthropology, …)
Computing
The Humanities
(Philosophy, History,
Linguistics …)
6
SCIENCES BASED ON SEVERAL RESEARCH FIELDS
– CROSS DISCIPLINARY RESEARCH
Our basic scheme represents classical sciences.
Many modern sciences however are stretching over several
research fields of our scheme.
Computer science e.g. includes the field of AI that has its roots in
mathematical logic and mathematics but uses physics, chemistry
and biology and even has parts where medicine and psychology
are very important.
Software Engineering include both formal methods and project
management.
HCI, human-computer interaction combines knowledge from “hard”
and “soft” sciences.
Computer games border with arts.
7
TECHNOLOGY
8
WRITING
THE ARCH
RAILWAYS
ELECTRICITY
COMPUTER
TELEVISION
AUTOMOBILE
CAMERA/TELESCOPE
SEWING MACHINE
INTERNET
ANTIBIOTICS
ANESTHETICS
DNA SEQUENCING
9
PROCESS OF VIRTUALIZATION IN TECHNOLOGY
http://www.youtube.com/watch?v=zh_8_iV4Plo&feature=related
Top 10 greatest inventions of mankind
http://www.youtube.com/watch?v=m2TkrC40VUc The History of
Information Technology
http://www.youtube.com/watch?v=Dg598hH_348
The History of Technological Innovations Video
10
TECHNOLOGY EXPANDS OUR WAYS OF
THINKING ABOUT THINGS, EXPANDS
OUR WAYS OF DOING THINGS.
Herbert A. Simon
11
SCIENCE AND SOCIETY
THE “TRIPLE HELIX” MODEL
SOCIETY
Knowledge society
based on ICT
CULTURE
SCIENCES & HUMANITIES
The triple helix model:
– ACADEMIA
– PRODUCTION
(ECONOMY)
– GOVERMENT
12
SOCIETAL ASPECTS OF SCIENCE
Science has several important facets:
- insights in foundational issues (understanding of the world)
- applications (practical use)
- societal aspects (impact on the society)
Sciences are promoting rational and analytical discussions of the
central issues of concern to scientists and other scholars, and to
the public at large, both in terms of knowledge production and in
practical applications.
13
SOCIETAL ASPECTS OF SCIENCE
RESEARCH COMMUNITY AS INFORMATIONAL NETWORK
“ .. if we consider Galileo alone in
his cell muttering, ‘and yet it
moves,’ with the recent meeting
at Kyoto – where heads of
states, lobbyists, and scientists
were assembled together in the
same place to discuss the Earth
– we measure the difference ..”
Bruno Latour
14
SOCIETAL ASPECTS OF SCIENCE
Further reading on current topics:
http://www.sciencemag.org
Essays on Science and Society
Science magazine
15
POSTMODERNISM AND THE NATURE OF SCIENCE
Modernism may be seen as the height of the Enlightenment's*
quest for an rational knowledge, aesthetics, and ethics.
Postmodernism is a cultural and philosophical movement which
formed in reaction to modernism.
Postmodernism is concerned with how the authority of rational
ideals, sometimes called meta-narratives**, are undermined
through fragmentation and deconstruction.
*The Age of Enlightenment (or simply the Enlightenment or Age of Reason) was a cultural
movement of intellectuals in 18th century Europe, that sought to mobilize the power of reason in
order to reform society and advance knowledge. It promoted intellectual interchange and opposed
intolerance and abuses in Church and state.
**Meta-narratives - "grand narratives“, form of ‘universal truth'
16
POSTMODERNISM
Postmodernism attacks the primacy of ideas of universals and
encourages fractured, fluid and multiple perspectives and is
marked by an increasing importance in the ideas from the
Sociology of knowledge.
17
POSTMODERNISM
All knowledge, scientific knowledge included, is found to be socially
constructed. Being “socially constructed” implies not absolute, but
relative to the humans and humanity. No (absolute) objectivity
exists for humans (or any other intelligent agents).
From that correct observation, postmodernist draw a very farreaching conclusion: “Science is merely one story among others.”
The world we know is one that is constructed by human discourses.
(correct) From the point of view of knowledge (epistemologically ),
a scientific text is understood as being on a par with a literary text.
(false)
18
TWO CULTURES
2009 marked the 50th anniversary of C. P. Snow’s famous “Two
Cultures” essay, in which he lamented the great cultural divide
that separates two great areas of human intellectual activity,
“science” and “the arts.”
Snow argued that practitioners in both areas should build
bridges, to further the progress of human knowledge and to
benefit society.
http://www.scientificamerican.com/article.cfm?id=an-update-on-cp-snows-two-cultures Image: Matt Collins
http://www.nytimes.com/2009/03/22/books/review/Dizikes-t.html?pagewanted=all Our Two Cultures
http://en.wikipedia.org/wiki/Consilience_(book) Consilience: The Unity of Knowledge is a 1998 book by biologist E.
O. Wilson.
19
SCIENCE WARS (1)
In early 1996 the physicist Alan Sokal who was provoked by
postmodernist negative attitude to science caused a controversy by
publishing two provocative journal articles.
The first article, Transgressing the Boundaries: Toward a
Transformative Hermeneutics of Quantum Gravity appeared in the
journal Social Text.
It pretended to be a serious article on the implications of
developments in the field of cultural studies for developments in
modern physics, and vice-versa.
20
SCIENCE WARS (2)
The second article, A Physicist Experiments with Cultural Studies,
appeared in the journal Lingua Franca just as issue of Social Text
containing the first article was published. It revealed that the first
article was a hoax.
21
SCIENCE WARS (3)
But why did Sokal do it? He says:
“I'm a stodgy old scientist who believes, naively, that there exists
an external world, that there exist objective truths about that world,
and that my job is to discover some of them. “
Allan Sokal
22
SCIENCE WARS (4)
“To test the prevailing intellectual standards, I decided to try a
modest (though admittedly uncontrolled) experiment:
Would a leading North American journal of cultural studies (..)
publish an article liberally salted with nonsense if
(a) it sounded good and
(b) it flattered the editors' ideological preconceptions? “
Allan Sokal
23
SCIENCE WARS (5)
The post modern ideas were known as Social Constructivism and
Deconstructionism.
The branch of sociology, Sociology of Scientific Knowledge (SSK) and
Science and Technology Studies (STS) were influences by postmodern
movements and had the objective of showing that the results of
scientific findings did not represent objective reality, but were basically
instruments of the ideology of dominant groups within society.
24
POSTMODERNIST ANTI-SCIENTISM
Post-modernism was a radical critique against science,
contemporary philosophy and current understanding of rationality.
The view of science as a search for truths (or approximate truths)
about the world was rejected.
According to postmodernism, the natural world has a subordinated
role in the construction of scientific knowledge.
Science was just another social practice, producing ``narrations''
and ``myths'' with basically no more validity than any other myths.
25
IS THERE ANYTHING NEW UNDER THE SUN?
ANY PROGRESS?
26
AN EXAMPLE OF PROGRESS - TRANSPORTATION
27
AN EXAMPLE OF PROGRESS - TRANSPORTS
“Beam me up Scotty” next?
28
SCIENCE WARS (6)
Sources for further reading:
http://www.physics.nyu.edu/faculty/sokal
http://www.math.gatech.edu/~harrell/cult.html
http://skepdic.com/sokal.html
29
WHAT HAVE WE LEARNED FROM
POSTMODERNISM?
Humans always produce theories that are context-dependent and
based on our (human) perspective. It is good to be aware of that
context in which science operates.
Society is an important factor when it comes to politics, including
policies in science which provide resources for science.
In a given context, by scientific methods we can reach our best
knowledge, which is constantly improving.
If not seen as absolute, but our best common knowledge about
the physical world, science has a very distinct position among
different possible descriptions of the world.
30
END OF SCIENCE WARS
AND NEW EMERGING ALLIANCES
At present, a lot of activity in cross-disciplinary, multi-disciplinary
and inter-disciplinary collaborations.
Examples: Computing and Philosophy http://ia-cap.org
and
Interdisciplines (Topics: Adaptation and Representation, Art and
Cognition, Causality, Enaction (Action and perception intertwined),
Issues in Coevolution of Language and Theory of Mind.)
http://www.interdisciplines.org
31
RESEARCH, COMMUNICATION AND ICT
New development of collaborations
between different research
disciplines is enabled by the
progress of technology.
However, there is a problem of
communication: Different
knowledge fields traditionally have
different languages.
32
RESEARCH, COMMUNICATION AND ICT
Sciences cover well defined domains
(physics, mathematics, biology,
sociology, economy…) where
knowledge is produced by specific
scientific communities through intense
communication within a group and with
not much communication with the rest
of the world.
However, access to knowledge have
become easy and communication
between sciences, arts and humanities
more and more common.
33
Cybernetics as a Language for
Interdisciplinary Communication
Stuart A. Umpleby
The George Washington University
Washington, DC
www.gwu.edu/~umpleby
34
HOW IS INTERDISCIPLINARY COMMUNICATION
POSSIBLE?
[Cybernetics is the interdisciplinary study of the structure of regulatory systems.
Cybernetics is closely related to control theory and systems theory. Both in its
origins and in its evolution in the second-half of the 20th century, cybernetics is
equally applicable to physical and social (that is, language-based) systems.
(Wikipedia)]
• We need to share a common language
• Perhaps there is a common “deep structure” which is hidden by
our more specialized discipline-oriented terms and theories
After Stuart A. Umpleby
35
COMMON PROCESSES IN THE EXTERNAL WORLD
James G. Miller’s suggests that living systems exist at seven levels:
- cell,
- organ,
- organism,
- group,
- organization,
- nation,
- supranational organization
After Stuart A. Umpleby
36
BASIC CONCEPTS
In cybernetics there are three fundamental concepts:
Regulation
Self-organization
Reflexivity
After Stuart A. Umpleby
37
REGULATION
Regulation is based on two elements – regulator and system
being regulated
Engineering examples – thermostat and heater, automatic pilot
and airplane
Biological examples – feeling of hunger and food in stomach,
light in eye and iris opening
Social system examples – manager and organization, therapist
and patient
After Stuart A. Umpleby
38
THE LAW OF REQUISITE VARIETY
Information and selection
“The amount of selection that can be performed is limited by
the amount of information available”
Regulator and regulated
“The variety in a regulator must be equal to or greater than the
variety in the system being regulated”
W. Ross Ashby
After Stuart A. Umpleby
39
COPING WITH COMPLEXITY
When faced with a complex situation, there are two choices
1. Increase the variety in the regulator: hire staff or
subcontract
2. Reduce the variety in the system being regulated: reduce
the variety one chooses to control
After Stuart A. Umpleby
40
THE MANAGEMENT OF COMPLEXITY
• There has been a lot of discussion of complexity, as if it exists in
the world
• Cyberneticians prefer to speak about “the management of
complexity”
• Their view is that complexity is observer dependent, that the
system to be regulated is defined by the observer
After Stuart A. Umpleby
41
SELF-ORGANIZATION
• Every isolated, determinate, dynamic system obeying
unchanging laws will develop organisms adapted to their
environments. W. Ross Ashby
• Many elements within the system
• Boundary conditions
– open to energy (hence dynamic)
– structures closed to information (interaction rules do not
change during the period of observation)
http://www-lih.univlehavre.fr/~bertelle/cossombook/cossombook.html
Complex Systems and Self-organization Modelling
After Stuart A. Umpleby
42
Examples of self-organization
Physical example – chemical reactions;
iron ore, coke, and oxygen heated in a
blast furnace will change into steel,
carbon dioxide, water vapor and slag
Biological examples – food in the
stomach is transformed into usable
energy and materials, species compete
to yield animals adapted to their
environments, insect swarms
After Stuart A. Umpleby
43
SELF-ORGANIZATION IN ARTIFACTS
http://groups.csail.mit.edu/mac/projects/amorphous/Robust Biologicallyinspired Models of Cell Differentiation and Morphogenesis
http://www.youtube.com/watch?v=SkvpEfAPXn4 Robots with minds of
their own
http://www.calresco.org/links.htm Self-organization resources
44
DIGITAL VIDEO FEEDBACK AND MORPHOGENESIS
Video Feedback systems tend toward either
stability or chaos. The unstable attractor
offers an unlimited supply of endless
evolving motifs and an emergent behaviour.
The system can be get into chaotic
emergence via camera movement (rotation
and positioning). The important thing is to
catch the movement of ‘catching a shape’ in
a particular temporal phase to feed back
into the system advancing the complexity
and initiating lifelike morphogenesis.
http://www.transphormetic.com/Talysis01.htm
45
COMPLEX SYSTEMS
http://www.youtube.com/watch?v=QmrWfRX42ZM&feature=related
Self-organizing adaptive systems
http://www.youtube.com/watch?v=ueJ0E-H7hkk&feature=related
Regime shifts
Four Important Characteristics of Complexity:
• Self-Organization
• Non-Linearity
• Order/Chaos Dynamic
• Emergent Properties
http://www.calresco.org/links.htm
46
COMPLEX SYSTEMS
Computer Programming approaches used for
demonstrating, simulating, and analyzing Complex
Systems:
• Artificial Life
• Genetic Algorithms
• Neural Networks
• Cellular Automata
• Boolean Networks
http://www.calresco.org/links.htm
47
SELF-REFERENCE
http://www.lsd.ic.unicamp.br/~oliva/guarana/docs/design-html/node2.html
Computational Reflection
48
DOUGLAS HOFSTADTER ON SELF-REFERENCE
“
Self-reference is ubiquitous. It happens every time any
one says “I” or “me” or “word” or “speak” or “mouth”. It
happens every time a newspaper prints a story about
reporters, every time someone writes a book about
writing, designs a book about book design, makes a
movie about movies, or writes an article about selfreference. Many systems have the capability to
represent or refer to themselves somehow, to
designate themselves (or elements of themselves)
within the system of their own symbolism. Whenever
this happens, it is an instance of self-reference.”
“My proposal [...] is to see the “I” as a hallucination
perceived by a hallucination, which sounds pretty
strange, or perhaps even stranger: the “I” as a
hallucination hallucinated by a hallucination.”
(I Am a Strange Loop, p. 293 )
49
SELF-REFERENCE (REFLEXIVITY)
This model has traditionally been
avoided and is logically difficult.
Inherent in social systems where
observers are also participants, in
individual living organisms.
Every statement reveals an
observer as much as what is
observed.
After Stuart A. Umpleby
50
EXAMPLES OF SELF-REFERENCE:
RECURSIVE ALGORITHMS
This graph is based on a simple
recursive algorithm. Recursion is
a popular technique used to
describe trees and the like,
because of the self-referential
nature of a tree.
Self-reference can lead to
undecidability (and paradoxes
like set of all sets that are not
members of themselves)
51
Self-reference (Reflexivity)
Observation
Self-awareness
After Stuart A. Umpleby
52
Reflexivity in a social system
Stuart A. Umpleby
53
Engineering Cybernetics
Biological Cybernetics
Social Cybernetics
The view of
epistemology
A realist view
of epistemology:
knowledge is a
“picture” of reality
A biological view of
epistemology: how the
brain functions
A pragmatic view of
epistemology:
knowledge is
constructed to achieve
human purposes
A key distinction
Reality vs. scientific
theories
Realism vs. Constructivism
The biology of cognition vs.
the observer as a
social participant
The puzzle to be
solved
Construct theories which
explain observed
phenomena
Include the observer within the
domain of science
Explain the relationship
between the natural
and the social sciences
What must be
explained
How the world works
How an individual constructs a
“reality”
How people create,
maintain, and change
social systems through
language and ideas
A key assumption
Natural processes can be
explained by
scientific theories
Ideas about knowledge should
be rooted in
neurophysiology.
Ideas are accepted if they
serve the observer’s
purposes as a social
participant
An important
consequence
Scientific knowledge can
be used to modify
natural processes to
benefit people
If people accept constructivism,
they will be more tolerant
By transforming conceptual
systems (through
persuasion, not
coercion), we can
change society
Three Versions of Cybernetics
54
After Stuart A. Umpleby
CYBERNETICS VIEW OF SCIENTIFIC
PROGRESS:
THE CORRESPONDENCE PRINCIPLE
Proposed by Niels Bohr when developing the quantum theory.
Any new theory should reduce to the old theory to which it
corresponds for those cases in which the old theory is known to hold
A new dimension is required
After Stuart A. Umpleby
55
NEW PHILOSOPHY OF SCIENCE
Old philosophy of
science
Amount of attention
paid to the observer
An Application of the Correspondence Principle
After Stuart A. Umpleby
56
NEW PARADIGM OF COMPUTING:
Organic computing
Organic computing is a form of biologically-inspired computing
with organic properties. It has emerged recently as a
challenging vision for future information processing systems.
Organic Computing is based on the insight that we will soon be
surrounded by large collections of autonomous systems, which
are equipped with sensors and actuators, aware of their
environment, communicate freely, and organise themselves in
order to perform the actions and services that seem to be
required.
http://en.wikipedia.org/wiki/Organic_computing
57
ORGANIC COMPUTING
The presence of networks of intelligent systems in our environment
opens fascinating application areas but, at the same time, bears
the problem of their controllability.
Hence, we have to construct such systems — which we
increasingly depend on — as robust, safe, flexible, and
trustworthy as possible.
In particular, a strong orientation towards human needs as opposed
to a pure implementation of the technologically possible seems
absolutely central.
In order to achieve these goals, our technical systems will have to
act more independently, flexibly, and autonomously, i.e. they will
have to exhibit life-like properties. We call those systems
"organic".
58
ORGANIC COMPUTING
• An "Organic Computing System" is a technical system, which
adapts dynamically to the current conditions of its environment.
It is characterised by the self-X properties:
• self-organization,
• self-configuration (auto-configuration),
• self-optimisation (automated optimization),
• self-healing,
• self-protection (automated computer security),
• self-explaining,
• and context-awareness.
59
ORGANIC COMPUTING
• In order to be able to build huge intelligent organic-computing
systems we have to learn from variety of fields – from physics,
chemistry, genetics, biology to sociology and linguistics.
• In other words we have to learn to manage complexity of
knowledge production from different research fields.
60
CONCLUSIONS:
TRANSDISCIPLINARY, INTERDISCIPLINARY AND CROSS
DISCIPLINARY RESEARCH
Modern sciences are stretching through several classical fields.
Computer science e.g. includes the field of AI that has its roots in
mathematical logic and mathematics but uses physics, chemistry
and biology and even parts where medicine and psychology are
important.
Examples: Environmental studies, Cognitive sciences, Cultural
studies, Policy sciences, Information sciences, Women’s studies,
Molecular biology, Philosophy of Computing and Information,
Bioinformatics, ..
61
CONCLUSIONS:
TRANSDISCIPLINARY, INTERDISCIPLINARY AND CROSS
DISCIPLINARY RESEARCH
Research into complex phenomena has led to an insight that
research problems have many different facets which may be
approached differently at different levels of abstraction and that
every knowledge field has a specific domain of validity.
This new understanding of a multidimensional many-layered
knowledge space have among others resulted in an ecumenical
conclusion of science wars by recognition of the necessity of an
inclusive and complex knowledge architecture which recognizes
importance of a variety of approaches and types of knowledge.
62
REPRESENTATIVE WORK:
TRANSDISCIPLINARY, INTERDISCIPLINARY AND CROSS
DISCIPLINARY RESEARCH
Based on sources in philosophy,
sociology, complexity theory, systems
theory, cognitive science, evolutionary
biology and fuzzy logic, Smith and Jenks
present a new interdisciplinary perspective
on the self-organizing complex structures.
They analyze the relationship between the
process of self-organization and its
environment/ecology. Two central factors
are the role of information in the formation
of complex structure and the development
of topologies of possible outcome spaces.
63
REPRESENTATIVE WORK:
TRANSDISCIPLINARY, INTERDISCIPLINARY AND CROSS
DISCIPLINARY RESEARCH
The authors argue for a continuous development from emergent
complex orders in physical systems to cognitive capacity of living
organisms to complex structures of human thought and to
cultures.
This is a new understanding of unity of interdisciplinary
knowledge, unity in structured diversity, also found in Mainzer.
64
REPRESENTATIVE WORK
“Cosmic evolution leads from
symmetry to complexity by
symmetry breaking and phase
transitions. The emergence of
new order and structure in nature
and society is explained by
physical, chemical, biological,
social and economic selforganization, according to the
laws of nonlinear dynamics.
All these dynamical systems are
considered computational
systems processing information
and entropy.”
65
REPRESENTATIVE WORK
“Are symmetry and complexity only useful models of science
or are they universals of reality? Symmetry and Complexity
discusses the fascinating insights gained from natural, social
and computer sciences, philosophy and the arts.
With many diagrams and pictures, this book illustrates the
spirit and beauty of nonlinear science. In the complex world of
globalization, it strongly argues for unity in diversity.”
66
REPRESENTATIVE WORK
ix
Preface
Part I
The Simple and the
Complex
1
Prologue: An Encounter in
the Jungle
2
Early Light
11
3
Information and Crude
Complexity
23
4
Randomness
43
5
A Child Learning a
Language
51
6
Bacteria Developing Drug
Resistance
63
7
The Scientific Enterprise
75
8
The Power of Theory
89
9
What Is Fundamental?
10
7
3
67
Part II
10
11
The Quantum Universe
Simplicity and Randomness in
the Quantum Universe
A Contemporary View of
Quantum Mechanics:
135
Quantum Mechanics and the
Classical Approximation
Quantum Mechanics and
Flapdoodle
167
13
Quarks and All That: The
Standard Model
177
14
Superstring Theory: Unification
at Last?
199
Time's Arrows: Forward and
Backward Time
Selection and Fitness
16
Selection at Work in Biological
Evolution and Elsewhere
235
17
From Learning to Creative
Thinking
261
18
Superstition and Skepticism
275
19
Adaptive and Maladaptive
Schemata
291
20
Machines That Learn or Simulate
Learning
307
123
12
15
Part III
215
Part IV Diversity and Sustainability
21
Diversities Under Threat
329
22
Transitions to a More Sustainable
World
345
23
Afterword
367
68
REPRESENTATIVE WORK
Philosophy of Information
(Handbook of the Philosophy of
Science) (Hardcover)
by Pieter Adriaans & Johan F.A.K. van
Benthem (Editors), 2008
DM. Gabbay, P Thagard & J Woods
(Series Editors)
69
Philosophy of Science/Theory of Science Assignments
– Assignment 2: Demarcation of Science vs. Pseudoscience (in
groups of two)
– Discussion of Assignment 2 - compulsory
– Assignment 2-extra (For those who miss the discussion of the
Assignment 2)
– Assignment 3: GOLEM: Three Cases of Theory Confirmation (in
groups of two)
– Discussion of Assignment 3 - compulsory
– Assignment 3-extra (For those who miss the discussion of the
Assignment 3)
70
AND AN EXAMPLE OF THE ROLE OF PERSPECTIVE
AT THE END!
71